Selected Projects
Technical products and data platforms I have built.
Placeholder image representing the interactive map interface and market comparison views from the Areaview.ai platform.
Areaview.ai
Flagship ProjectGeospatial Real Estate Market Analytics Platform
Areaview.ai was a geospatial analytics platform designed to help real estate investors evaluate housing markets more efficiently. The platform aggregated hundreds of economic, demographic, and housing metrics and visualized them through an interactive map interface, allowing users to compare potential investment locations across the United States.
Key Metrics
Problem
Real estate investment research requires information from many fragmented sources such as housing prices, rent trends, demographics, crime statistics, and economic indicators. Collecting and comparing this data across multiple markets can require many hours of manual research.
Areaview.ai was designed to centralize this information and allow users to explore markets through a unified geospatial interface.
Platform Features
Pan, zoom, and explore housing markets through a responsive geospatial interface.
Search by neighborhood, census tract, or ZIP code to compare locations side by side.
Generate exportable summaries with key metrics and charts for any selected area.
Surface composite indicators that highlight relative opportunity and risk.
Enable investors and collaborators to discuss markets directly inside the platform.
Technical Stack
Frontend
Geospatial Visualization
Backend & Infrastructure
Authentication & Messaging
Data Sources
The platform combined public and commercial datasets to provide a multi-dimensional view of local housing markets.
Engineering Challenges
Rendering large geospatial datasets efficiently was one of the most difficult engineering problems. The platform needed to visualize thousands of geographic polygons while maintaining fast and responsive map interactions.
Additional challenges included handling changing census boundaries across years and aggregating metrics across multiple geographic levels without losing spatial accuracy.
Outcome & Lessons
Although the platform demonstrated large-scale geospatial data integration and full-stack development, it did not ultimately succeed commercially.
The primary challenge was customer acquisition rather than technical feasibility. The project nevertheless provided extensive experience in geospatial data engineering, full-stack application architecture, and building large-scale data platforms.